Daisy Stanton
- Artificial Intelligence top 5%
- Signal Processing top 5%
- Computer Vision and Pattern Recognition
- Experimental and Cognitive Psychology
- Control and Systems Engineering
- Co-authors
- RJ Skerry-RyanYuxuan WangRif A. SaurousYing XiaoRichard ZensPeng XuEric BattenbergSamy Bengio
- Topics
- Speech Recognition and Synthesis (5 papers)Natural Language Processing Techniques (4 papers)Speech and dialogue systems (4 papers)
- Journals
- Empirical Methods in Natural Language ProcessingarXiv (Cornell University)International Conference on Machine Learning
- Partner nations
- United StatesChina
In The Last Decade
Daisy Stanton
6 papers receiving 229 citations
Peers
Comparison fields: 5 of 18
- Artificial Intelligence 247
- Signal Processing 142
- Computer Vision and Pattern Recognition 22
- Experimental and Cognitive Psychology 10
- Control and Systems Engineering 4
Countries citing papers authored by Daisy Stanton
This map shows the geographic impact of Daisy Stanton's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daisy Stanton with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daisy Stanton more than expected).
Fields of papers citing papers by Daisy Stanton
This network shows the impact of papers produced by Daisy Stanton. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daisy Stanton. The network helps show where Daisy Stanton may publish in the future.
Co-authorship network of co-authors of Daisy Stanton
This figure shows the co-authorship network connecting the top 25 collaborators of Daisy Stanton. A scholar is included among the top collaborators of Daisy Stanton based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daisy Stanton. Daisy Stanton is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 11 | |
| 2 | Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis | 62 |
| 3 | 73 | |
| 4 | Tacotron: A Fully End-to-End Text-To-Speech Synthesis Model. | 86 |
| 5 | 4 | |
| 6 | A Systematic Comparison of Phrase Table Pruning Techniques | 29 |
About Daisy Stanton
Daisy Stanton is a scholar working on Artificial Intelligence, Signal Processing and Infectious Diseases, having authored 6 papers that have together received 265 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (5 papers), Natural Language Processing Techniques (4 papers) and Speech and dialogue systems (4 papers). The work is most often cited by research in Signal Processing (142 citations), Artificial Intelligence (247 citations) and Computer Vision and Pattern Recognition (22 citations). Daisy Stanton has collaborated with scholars based in United States and China. Frequent co-authors include RJ Skerry-Ryan, Yuxuan Wang, Rif A. Saurous, Ying Xiao, Richard Zens, Peng Xu, Eric Battenberg, Samy Bengio, Yonghui Wu and Quoc V. Le. Their work appears in journals such as Empirical Methods in Natural Language Processing, arXiv (Cornell University) and International Conference on Machine Learning.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.